DP-203 Design and implement data storage Practice Question
This DP-203 practice question tests your understanding of design and implement data storage. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
You are designing a change data capture (CDC) pipeline to ingest incremental changes from an on-premises SQL Server database into Azure Data Lake Storage Gen2. The pipeline must run every 5 minutes and handle high-volume DML changes. Which Azure service should you use to capture the changes with low latency?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Azure Data Factory with a change data capture (CDC) source in the mapping data flow.
Azure Data Factory's mapping data flow includes a native CDC source that can connect to SQL Server and capture incremental DML changes (inserts, updates, deletes) with low latency. This approach uses change tracking or change data capture features in SQL Server to identify changes, and the pipeline can run every 5 minutes to meet the high-volume requirement without custom coding.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
✗
Azure Data Share to share the SQL Server data and capture changes.
Why it's wrong here
Data Share is for sharing snapshots, not real-time CDC.
✓
Azure Data Factory with a change data capture (CDC) source in the mapping data flow.
Why this is correct
ADF supports CDC from SQL Server with low latency via mapping data flows.
Related concept
Read the scenario before looking for a memorised answer.
✗
Azure Synapse Pipelines with a copy activity that uses a query to capture changes.
Why it's wrong here
Though possible, ADF is the primary service for CDC pipelines.
✗
Azure Databricks with Auto Loader and Delta Live Tables to capture changes.
Why it's wrong here
Auto Loader is for file ingestion, not for database CDC.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse Azure Data Factory's copy activity (which requires manual change tracking) with the mapping data flow's native CDC source, leading them to choose option C or D, which are better suited for different ingestion patterns.
Detailed technical explanation
How to think about this question
Azure Data Factory's CDC source in mapping data flow leverages SQL Server's change tracking feature (not full CDC) to detect row-level changes, using a low-overhead mechanism that tracks version numbers. The pipeline can be configured to run every 5 minutes, and the mapping data flow engine applies net changes (inserts, updates, deletes) to the destination in a single pass, ensuring consistency even under high-volume DML loads. A real-world scenario where this matters is when you need to maintain a near-real-time copy of a transactional database for analytics without overloading the source system.
KKey Concepts to Remember
Read the scenario before looking for a memorised answer.
Find the constraint that changes the correct option.
Eliminate answers that are true in general but not in this case.
TExam Day Tips
→Watch for words such as best, first, most likely and least administrative effort.
→Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
Related glossary terms
Concepts from this question explained
These glossary pages explain the core terms tested in this DP-203 question in full detail.
Design and implement data storage — This question tests Design and implement data storage — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Azure Data Factory with a change data capture (CDC) source in the mapping data flow. — Azure Data Factory's mapping data flow includes a native CDC source that can connect to SQL Server and capture incremental DML changes (inserts, updates, deletes) with low latency. This approach uses change tracking or change data capture features in SQL Server to identify changes, and the pipeline can run every 5 minutes to meet the high-volume requirement without custom coding.
What should I do if I get this DP-203 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Question Discussion
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